viernes, 28 de noviembre de 2014

Perceptron training visualization

Visualization of a Perceptron trying to classify samples into two different categories.

In this representation there is no bias involved, the green arrow are the model
weights and it defines an hyperplane orthogonal to them centred in the
coordinates [0,0]. In each iteration the sample being tested is shown in
orange. If the sample is in the wrong side of the hyperplane the vector
representing the sample is shown, then the red vector is the same vector
reescaled by the learning rate and it is summed to the weights vector. Then,
the next sample is tested.